phData

NOVEMBER 4, 2024

It must integrate seamlessly across data technologies in the stack to execute various workflows—all while maintaining a strong focus on performance and governance. Two key technologies that have become foundational for this type of architecture are the Snowflake AI Data Cloud and Dataiku. Let’s say your company makes cars.

Machine Learning 69

Machine Learning Machine Learning Data Science ML 69

ODSC - Open Data Science

APRIL 15, 2025

LLMs, AI agents, and generative AI are the buzzwords lighting up the data science world. But if youre serious about working with LLMs or any advanced AI system, you need to start at the foundation. Before you dive into prompt engineering or fine-tuning, its essential to master the AI basics and data science fundamentals.

Data Wrangling 52

Data Wrangling Data Science AI AI 52

How to Learn Machine Learning

APRIL 26, 2025

It’s not simply about the numbers, but how they can communicate the story behind the data to then model complex datasets into insights that stakeholders can act on. With so many diverse data science career paths, sometimes making up one’s mind about the right career choice in this field seems overwhelming.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

Pickl AI

APRIL 21, 2025

This is where Big Data often comes into play as the source material. Cleaning and Preparing the Data (Data Wrangling) Raw data is almost always messy. This often takes up a significant chunk of a data scientist’s time. Think graphs, charts, and summary statistics.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

Mlearning.ai

JULY 9, 2023

Goal The objective of this post is to demonstrate how Polars performance is much better than other open-source libraries in a variety of data analysis tasks, such as data cleaning, data wrangling, and data visualization. ? BECOME a WRITER at MLearning.ai // invisible ML // 800+ AI tools Mlearning.ai

Data Analysis 52

Data Analysis Data Analysis Python Data Scientist 52

Pickl AI

NOVEMBER 21, 2024

Step 2: Numerical Computation in MATLAB Once the data is cleaned, you can use MATLAB for heavy numerical computations. You can load the cleaned data and use MATLAB’s extensive mathematical functions for analysis. Load the cleaned data from the CSV file, and perform statistical tests or models like linear regression.

Python 52

Python Cloud Computing Machine Learning Machine Learning 52

Pickl AI

JULY 20, 2023

Here are some project ideas suitable for students interested in big data analytics with Python: 1. Kaggle datasets) and use Python’s Pandas library to perform data cleaning, data wrangling, and exploratory data analysis (EDA). Analyzing Large Datasets: Choose a large dataset from public sources (e.g.,

Analytics 40

Analytics Analytics Big Data Big Data 40